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Record W1952518244 · doi:10.1111/eip.12250

Understanding access and use of technology among youth with first‐episode psychosis to inform the development of technology‐enabled therapeutic interventions

2015· article· en· W1952518244 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEarly Intervention in Psychiatry · 2015
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsÉcole de Technologie SupérieureUniversité de MontréalDouglas Mental Health University InstituteCentre Hospitalier de l’Université de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychoeducationPsychological interventionPsychologyPsychosisApplied psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

AIM: Computers, video games and technological devices are part of young people's everyday lives. However, their use in first-episode psychosis (FEP) treatment is rare. The purpose of this study was to better understand the access and use of technology among individuals with FEP, including gaming activities, to inform future development of technology-enabled therapeutic applications. METHODS: Self-administered survey on use of technological tools in 71 FEP individuals. RESULTS: PCs/laptops were used by all participants; cellphones/smartphones by 92%, consoles by 83% (mainly male and younger participants). Women texted and used social networks more frequently; men played games (mainly action) more often. The younger individuals reported playing games frequently (32% daily) with less use of the Web and social networks (favourite: Facebook). CONCLUSIONS: These data will be useful for developing Web-based psychoeducation tools and cognitive remediation video games for youth with FEP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.145
GPT teacher head0.362
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it